6G networks will host AI agents to automate enterprise workflows

Future 6G mobile networks will go beyond simple connectivity by hosting AI agents to automate complex enterprise workflows.

While 5G focused on bandwidth and latency, early standardisation work suggests the next generation of mobile infrastructure will function as a distributed intelligence platform, capable of interpreting business intent and coordinating autonomous actions across devices.

This evolution alters the role of the network from a passive data pipe to a proactive orchestration layer. A recent draft submitted to the Internet Engineering Task Force (IETF) details how operators plan to deploy “network AI agents” that interact with on-device and third-party agents to execute sophisticated tasks. This architectural change presents new opportunities for automation, but implies heavy requirements for identity management, security, and cross-domain governance.

6G networks: From connectivity to intent-based operations

The core value proposition from the 3GPP R20 standardisation research involves “intent-based” services. Rather than configuring technical parameters, users or enterprise systems express a goal (such as executing a rescue mission or ensuring connection quality for a specific meeting) and the network determines how to achieve it.

In a disaster recovery scenario, for instance, a command centre might issue an intent to “execute the rescue mission with multiple rescue robots in a certain area.” Upon receiving this request, 6G network-native AI agents initiate planning, decomposing the high-level goal into specific sub-tasks. These tasks include road obstacle sensing, route planning for multiple robots, and allocating communication resources to the disaster zone.

This capability reduces the burden on central cloud systems and allows decision-making closer to the edge. The network utilises its inherent sensing and computing services to support the agents, creating a tighter loop between perception and action. For logistics and field operations, this means the infrastructure itself handles real-time coordination, allowing human operators to focus on strategy rather than connectivity management.

Orchestrating cross-silo data with AI agents

The utility of this architecture extends to complex commercial environments where data sits in isolated silos. The IETF draft outlines a use case involving electric vehicle (EV) charging that demonstrates the potential for secure and cross-domain collaboration.

In this scenario, an EV’s on-device AI agent monitors energy prices and considers selling battery power back to the grid. Before executing, it securely accesses the calendars of the vehicle owners – hosted by different providers – to verify their travel plans. Upon learning of a planned 900km trip, the agent cancels the energy sale to ensure sufficient charge.

This level of automation requires strict privacy protocols. The document notes that all cross-border data exchanges must block unauthorised access, ensuring that an agent only retrieves data it is explicitly permitted to see. This highlights the necessity of “efficient collaboration” protocols that support multimodal data interactions while respecting data sovereignty.

Service exposure and new revenue streams

For telecom operators and their enterprise customers, 6G introduces a model where the network exposes more than just bandwidth. It offers “sensing services, computing services, and AI/ML services” directly to third-party applications.

Consider the operational requirements of autonomous transport. 3GPP operators possess unique advantages, including wide-area environmental data and distributed AI capabilities. A network-native AI assistant could interpret a vehicle’s intent for “safe navigation” and orchestrate necessary local inferencing or external data integration to fulfil that request.

Similarly, for business travellers, operators could provide customised service provisioning. If a user has an important online meeting scheduled during a train journey, the 6G network-native AI agent analyses the route, predicts coverage gaps, and pre-configures resources to ensure quality of experience (QoE). This moves Service Level Agreements (SLAs) from static contracts to agent-negotiated guarantees.

The governance imperative: Identity and reliability

However, integrating autonomous agents into the network fabric introduces substantial risk. The IETF draft emphasises that “security risks (malicious intent, intent misinterpretation) of AI agents are critical.” An improperly authenticated agent could disrupt network operations or leak sensitive corporate data.

To mitigate this, the standardisation body proposes a rigorous identity framework. The network must support “secure authentication, authorisation, and management mechanisms” specifically for AI agents, distinct from human users. This includes verifying the identity of on-device agents, third-party agents, and network agents before allowing them to interact.

Furthermore, reliability assurance becomes a mandatory component of the architecture. Because agent decisions can directly alter network configurations, operators must implement mechanisms such as “network digital twins” to validate decisions before execution. Only decisions verified for reliability can be allowed to change the network environment, preventing cascading failures caused by autonomous errors.

Preparing for AI agent-native infrastructure in the transition to 6G networks

The transition to 6G represents a major change in how enterprises will interact with telecom providers. The introduction of AI agents enables operators to leverage the full potential of mobile networks; improving efficiency and user experience.

Enterprise leaders should monitor the development of these agent communication-related protocols. Future procurement strategies will likely involve evaluating a provider’s ability to host or integrate with corporate AI agents. The separation of user identity from agent identity will also require updates to Identity and Access Management (IAM) policies to accommodate non-human entities that act on behalf of employees.

As the 3GPP R20 study progresses, the focus will sharpen on how these agents are registered, discovered, and managed. Success in this new environment will depend on establishing trust frameworks that allow diverse AI entities – from robot dogs to smart cameras – to collaborate without compromising network integrity or data privacy.

See also: Telecoms in 2026: Edge AI, data sovereignty, and monetisation

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Tags: 3gpp, 6g, ai, artificial intelligence, automation, connectivity, digital twins, Enterprise, infrastructure, networks, standards